scholarly journals SEGITIGA KEMISKINAN-PERTUMBUHAN-KETIMPANGAN (PGI TRIANGLE): PEMBANGUNAN KEUANGAN, PEMBANGUNAN MANUSIA, DAN KETIMPANGAN PENDAPATAN DI ASIA

2020 ◽  
Vol 28 (2) ◽  
pp. 77-89
Author(s):  
Rivanda Fadhila Indra Putra ◽  
Vera Lisna
Keyword(s):  
Income Inequality ◽  
Human Development ◽  
Financial Development ◽  
Low Income ◽  
Random Effect ◽  
Random Effect Model ◽  
Financial Sector ◽  
Fixed Effect Model ◽  
Effect Model ◽  
Panel Data Regression

One of the issues faced by countries in asia is income inequality. Economic development is expected to improvepeoples living standards to minimize the gap between low-income and high-income populations. One of economicdevelopment is through financial development. The financial sector plays an important role in the economy of acountry, the development of the financial sector will indirectly increase the output of other sectors so as to tie thevalue of the gross domestic product (gdp). In addition to equality and economic growth, economic developmentalso needs to see whether the two are related to human development as described in the poverty-growth-inequality triangle (pgi triangle). The purpose of this study is to see a picture of the inequality of income distribution, financial development and human development in six asian countries. The analysis used descriptive statistics and panel data regression, specifically fixed effect model (fem) and the random effect model (rem). The result showed that there is a significant influence between financial development and human development on income inequality, the higher the financial development will reduce the level of inequality of a country. Meanwhile, the high value of human development actually increases inequality.

scholarly journals Pengaruh Pendidikan, Pengangguran, dan Kemiskinan terhadap Ketimpangan Pendapatan di Indonesia

2019 ◽  
Vol 8 (3) ◽  
pp. 250
Author(s):  
Hindun Hindun ◽  
Ady Soejoto ◽  
Hariyati Hariyati
Keyword(s):  
Data Analysis ◽  
Income Inequality ◽  
Random Effect ◽  
Random Effect Model ◽  
Secondary Data ◽  
Ministry Of Education ◽  
Effect Model ◽  
Panel Data Regression ◽  
Analysis Technique ◽  
Data Regression

This research aims to analyze the effect of education, unemployment, and poverty on income inequality in Indonesia, both partially and simultaneously. This research uses secondary data with a quantitative approach. The type of research used is the type of associative research. The variables in this study are education, unemployment, poverty, and income inequality — data source from BPS and the Ministry of Education and Culture. The data analysis technique used is panel data regression analysis with cross-section 34 provinces and time series for 2015-2018. The results of the research obtained the random effect model, the best models. The results of data analysis show that education and poverty had a partial effect on income inequality in Indonesia, while unemployment had not to affect income inequality. Simultaneously, education, unemployment, and poverty affect income inequality in Indonesia. However, education, unemployment, and poverty can only explain 22.37% of the effect on income inequality in Indonesia. The rest is influenced by factors outside the model.

scholarly journals MODEL REGRESI DATA PANEL UNTUK MENGETAHUI FAKTOR YANG MEMPENGARUHI TINGKAT KEMISKINAN DI PULAU MADURA

2020 ◽  
Vol 9 (3) ◽  
pp. 355-363
Author(s):  
Artanti Indrasetianingsih ◽  
Tutik Khalimatul Wasik
Keyword(s):  
Panel Data ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Series Data ◽  
Poverty Level ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

Poverty arises when a person or group of people is unable to meet the level of economic prosperity which is considered a minimum requirement of a certain standard of living or poverty is understood as a state of lack of money and goods to ensure survival. Panel data regression is the development of regression analysis which is a combination of time series data and cross section data. Panel data regression is usually used to make observations of data that is examined continuously for several periods. The purpose of this study is to determine the factors that influence the level of poverty in Madura Island in the period 2008 - 2017. In this study the variables used in this study are life expectancy (X1), average length of school (X2), level open unemployment (X3), and labor force participation (X4) with the Comman Effect Model (CEM) approach, Fixed Effect Model and Random Effect Model (REM). To choose the best model from the three is the chow test, the hausman test and the breusch-pagan test. In this study, the best model chosen was the Fixed Effect Model. Keywords: CEM, Fixed Effect Model, Data Panel Regression, REM, Poverty level.

scholarly journals Flypaper Effect on Operating Expenditure and Capital Expenditure of the City Government in Indonesia

2015 ◽  
Vol 16 (1) ◽  
pp. 75
Author(s):  
Endah Purbarini ◽  
Gregorius N. Masdjojo
Keyword(s):  
Capital Expenditure ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
City Government ◽  
Flypaper Effect ◽  
Operating Expenditure ◽  
Effect Model ◽  
Panel Data Regression ◽  
The City

This research analyze the possibility of flypaper effect on Operating Expenditure (OE) and Capital Expenditure (CE) of the City Government in Indonesia. The research also tested the effect of the Original Regional Revenue (ORR) and the General Allocation Fund (GAF) against OE and CE in the period of 2010-2012. Types of data used was the data panel, which is a combination data 2010-2012 time series and cross section 56 city. This research used panel data regression analysis which is estimated by Fixed Effect Model (FEM) and Random Effect Model (REM). The results of this research indicate that the ORR and GAF have positive and significant effect on OE. Furthermore this research find that flypaper effect occurs in OE. But the GAF is not significant to the CE. The ORR have a positive and significant effect on CE. Furthermore this research find that flypaper effect does not occur on CE.

scholarly journals Pengaruh pad, dau, dak terhadap ipm dengan belanja modal sebagai variabel intervening (studi pada kabupaten/kota di provinsi papua tahun 2009 -2013)

2017 ◽  
Vol 22 (2) ◽  
Author(s):  
Ayu Aldi Raviyanti ◽  
Sri Rahayu ◽  
Dewa Putra Krishna Mahardika
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Capital Expenditure ◽  
Random Effect ◽  
Random Effect Model ◽  
Composite Index ◽  
Development Index ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

One way to measure the success or performance of a country or region in the field of human development used the Human Development Index (HDI). Human Development Index (HDI) is a composite index to measure the achievement of human development based on a number of basic components of quality of life. The purpose of this study is to determine how much Local Genuine Revenue (PAD), General Allocation Fund (DAU), Special Allocation Fund (DAK), Human Index Development (HDI) and Capital Expenditure in the Regencies/Cities of Papua Provinci for years 2009-2013, as well as determine the influence of PAD, DAU and DAK to HDI with Capital Expenditure as an intervening variable either simultaneously or partially. The method that used in this research is panel data regression using Random Effect Model (REM) with research period of year 2009-2013 using software Eviews 8.0. Total population in this research were 29 regencies/cities. By using purposive sampling, obtained sample of 24 regencies/cities. The results of this study indicate that PAD, DAU, and DAK jointly is influenced on Human Development Index with Capital Expenditure as an intervening variable. Partially, PAD is influenced of positive on HDI through Capital Expenditure, DAU is influenced of positive on HDI through Capital Expenditure, while DAK is not influenced on HDI through Capital Expenditure.

Tingkat Kemiskinan di Sumatra Selatan dan Analisisnya

2020 ◽  
Vol 8 (2) ◽  
pp. 127-133
Author(s):  
Doni Putra ◽  
Rifki Khoirudin
Keyword(s):  
Research Method ◽  
Random Effect ◽  
Random Effect Model ◽  
Poverty Rate ◽  
Variable Number ◽  
Regression Method ◽  
Poverty Level ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

This study aims to determine the factors that affect the poverty rate of regencies / cities in South Sumatra Province in 2011 to 2017. In this study the factors that affect poverty rates are related to unemployment, HDI, MSE, and population. The research method used is the panel data regression method using the help of Eviews software. The final thanks is the Random Effect Model. The results of this study are the variable Number of Population has a significant effect on the level of poverty in the District / City in South Sumatra Province. However, the Unemployment Rate Variable, HDI, and UMK were not significant to the poverty level in the regencies / cities in South Sumatra Province.

scholarly journals Analysis Of Effect Of ZIS (Zakat, Infaq, And Shadaqah), Regional Domestic Products Of Bruto, Regional Minimum Wage And Inflation On Levels Poverty In Indonesia 2012 – 2016

2019 ◽  
Vol 2 (2) ◽  
pp. 193-211
Author(s):  
Fiky Nila Mustika ◽  
Eni Setyowati ◽  
Azhar Alam
Keyword(s):  
Panel Data ◽  
Random Effect ◽  
Random Effect Model ◽  
Secondary Data ◽  
Minimum Wages ◽  
Effect Model ◽  
Panel Data Regression ◽  
The Impact ◽  
Poverty Levels ◽  
Domestic Products

This study investigated the impact of ZIS (Zakat, Infaq, and Sadaqah) Gross Regional Domestic Products, Regional Minimum Wages, and Inflation on Poverty Levels in Indonesia during the 2012-2016 period. .This paper used secondary data in the panel data form. This research conducted a quantitative approach using panel data regression. Based on the results of the panel data testing, the best model chosen is the Random Effect Model (REM). Variables of gross regional domestic products and regional minimum wages have a significant effect on poverty levels in Indonesia while the variables of zakat, infaq, and shadaqah (ZIS) and inflation do not influence the level of poverty in Indonesia.

scholarly journals The Correlation of Glycemic Index, Glycemic Load, and Carbohydrates with the Risk of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

2021 ◽  
Author(s):  
Long-Shan Yang ◽  
Guang-Xiao Meng ◽  
Zi-Niu Ding ◽  
Lun-Jie Yan ◽  
Sheng-Yu Yao ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Glycemic Index ◽  
Hepatitis Virus ◽  
Meta Analysis ◽  
Glycemic Load ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Case Control Studies ◽  
Effect Model

Abstract Background Glycemic index (GI), glycemic load (GL), and carbohydrates have been shown to be associated with a variety of cancers, but their correlation with hepatocellular carcinoma (HCC) remains controversial. The purpose of our study was to investigate the correlation of GI, GL and carbohydrate with risk of HCC.Methods Systematic searches were conducted in PubMed, Embase and Web of Science until November 2020. According to the size of heterogeneity, the random effect model or the fixed effect model was performed to calculate the pooled relative risks (RRs) and 95% confidence intervals (CIs) for the correlation of GI, GL, and carbohydrates with the risk of HCC.Results Seven cohort studies involving 1,193,523 participants and 1,004 cases, and 3 case-control studies involving 827 cases and 5,502 controls were eventually included. The pooled results showed no significant correlation of GI (RR=1.11, 95%CI 0.80-1.53, I2= 62.2%), GL (RR=1.09, 95%CI 0.76-1.55, I2 = 66%), and carbohydrate (RR=1.09, 95%CI 0.84-1.32, I2=0%) with the risk of HCC in general population. Subgroup analysis revealed that in hepatitis B virus (HBV) or/and hepatitis C virus (HCV)-positive group, GI was not correlated with the risk of HCC (RR=0.65, 95%CI 0.32-1.32, p=0.475, I2=0.0%), while GL was significantly correlated with the risk of HCC (RR=1.52, 95%CI 1.04-2.23, p=0.016, I2=70.9%). In contrast, in HBV and HCV-negative group, both GI (RR=1.23, 95%CI 0.88-1.70, p=0.222, I2=33.6%) and GL (RR=1.17, 95% CI 0.83-1.64, p=0.648, I2=0%) were not correlated with the risk of HCC. Conclusion A high GL diet is correlated with a higher risk of HCC in people with hepatitis virus. A low GL diet may be recommended for patients with viral hepatitis to reduce the risk of HCC.

scholarly journals PENGARUH PRODUK DOMESTIK BRUTO (PDB) DAN INDEKS PEMBANGUNAN MANUSIA (IPM) TERHADAP ANGKA KEMISKINAN DI INDONESIA

2010 ◽  
Vol 8 (2) ◽  
pp. 357
Author(s):  
Muhammad Sri Wahyudi Suliswanto
Keyword(s):  
Gross Domestic Product ◽  
Human Development ◽  
Human Development Index ◽  
Random Effect ◽  
Random Effect Model ◽  
Negative Influence ◽  
Domestic Product ◽  
Development Index ◽  
Effect Model ◽  
Independent Variable

Poverty is classic issue faced by most developing countries and is one of economic indicators to view public welfare level in any region. The research aimed to analyze effect of Gross Domestic Product (GDP), and human development index on poverty in Indonesia. Analysis used quantitative with Random Effect Model (REM) method in Panel Data with time series year 2006 to 2008. Anaysis result concluded that all independent variable simultaneously had significant effect on poverty variable in Indonesia and partially Gross Domestic Product (GDP) variable had significant negative influence on poverty with α 20%, and Human Development Index (HDI) variable had significant negative influence on poverty with α 5%.

scholarly journals DIVERSIFIKASI EKSPOR NON MIGAS INDONESIA KE PASAR NON TRADISIONAL

2020 ◽  
Vol 14 (2) ◽  
pp. 215-238
Author(s):  
Hotsawadi Harahap ◽  
Widyastutik
Keyword(s):  
United Arab Emirates ◽  
Oil And Gas ◽  
Random Effect ◽  
Random Effect Model ◽  
Structural Match ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Oil Exports

Abstrak Penelitian ini bertujuan untuk menganalisis diversifikasi ekspor non migas Indonesia ke pasar non tradisional. Metode penelitian yang digunakan adalah analisis statistik deskriptif dengan pendekatan pengelompokan (clustering), Structural Match Index dan Demand Index, serta regresi data panel. Hasil penelitian menunjukkan bahwa negara yang diidentifikasikan sebagai negara non tradisional potensial adalah Brazil, Pantai Gading, Mesir, Georgia, Jamaica, Kazakhstan, Kuwait, Myanmar, Nigeria, Norway, Oman, Pakistan, Russian Federation, Trinidad and Tobago, Turkey, United Arab Emirates, dan Uruguay. Hasil regresi data panel menunjukkan bahwa Random Effect Model merupakan model yang terbaik untuk menjelaskan faktor-faktor yang memengaruhi ekspor non migas Indonesia ke negara non tradisional. Hasil regresi menunjukkan bahwa GDP riil negara tujuan, populasi negara tujuan, nilai tukar riil, FDI dan kualitas pelabuhan Indonesia berpengaruh signifikan secara statistik terhadap ekspor non migas Indonesia ke negara non tradisional potensial tersebut. Beberapa rekomendasi kebijakan yang perlu dilakukan untuk meningkatkan ekspor non migas ke negara tujuan non tradisional diantaranya perlu dilakukan intelejen pasar mengenai kebutuhan dan selera dari masing-masing negara non tradisional atas produk Indonesia, peningkatan kualitas pelabuhan Indonesia dan kebijakan tambahan yang memberikan insentif untuk menarik Foreign Direct Investment ke Indonesia. Kata Kunci: Diversifikasi Ekspor, Demand Index, Non traditional, Random Effect Model, Structural Match Index   Abstract This study aims to analyze the diversification of Indonesia's non-oil and gas exports to non-traditional markets. The research method used is descriptive statistical analysis with a clustering approach, Structural Match Index and demand index, and panel data regression. The results showed that countries identified as potential non-traditional countries were Brazil, Ivory Coast, Egypt, Georgia, Jamaica, Kazakhstan, Kuwait, Myanmar, Nigeria, Norway, Oman, Pakistan, Russian Federation, Trinidad and Tobago, Turkey, United Arab Emirates, and Uruguay. The panel data regression results show that the random effect model is the best model to explain the factors that influence Indonesia's non-oil exports to non-traditional countries. The results show that the real GDP of the destination country, the population of the destination country, the real exchange rate, FDI and the quality of Indonesia's ports have a statistically significant effect on Indonesia's non-oil exports to these potential non-traditional countries. Then, in this study there are several policy recommendations that need to be done to increase non-oil and gas exports to non-traditional destination countries including market intelligence regarding the needs and tastes of each non-traditional country for Indonesian products, improving the quality of Indonesian ports and additional policies that provide incentives to attract Foreign Direct Investment to Indonesia. Keywords:  Export Diversification, Demand Index, Non-traditional, Random Effect Model, Structural Match Index JEL Classifications: F13, F15, F18

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